How to connect Facebook and Google Cloud BigQuery (REST)
Create a New Scenario to Connect Facebook and Google Cloud BigQuery (REST)
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Facebook, triggered by another scenario, or executed manually (for testing purposes). In most cases, Facebook or Google Cloud BigQuery (REST) will be your first step. To do this, click "Choose an app," find Facebook or Google Cloud BigQuery (REST), and select the appropriate trigger to start the scenario.

Add the Facebook Node
Select the Facebook node from the app selection panel on the right.

Configure the Facebook
Click on the Facebook node to configure it. You can modify the Facebook URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Cloud BigQuery (REST) Node
Next, click the plus (+) icon on the Facebook node, select Google Cloud BigQuery (REST) from the list of available apps, and choose the action you need from the list of nodes within Google Cloud BigQuery (REST).

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Authenticate Google Cloud BigQuery (REST)
Now, click the Google Cloud BigQuery (REST) node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud BigQuery (REST) settings. Authentication allows you to use Google Cloud BigQuery (REST) through Latenode.
Configure the Facebook and Google Cloud BigQuery (REST) Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Facebook and Google Cloud BigQuery (REST) Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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Save and Activate the Scenario
After configuring Facebook, Google Cloud BigQuery (REST), and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Facebook and Google Cloud BigQuery (REST) integration works as expected. Depending on your setup, data should flow between Facebook and Google Cloud BigQuery (REST) (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Facebook and Google Cloud BigQuery (REST)
Facebook + Google Cloud BigQuery (REST) + Google Sheets: This workflow analyzes Facebook ad performance by pulling data, storing it in BigQuery, and then visualizing key metrics in Google Sheets.
Google Cloud BigQuery (REST) + Slack: When a new row is added to a BigQuery table containing social media data, an alert is posted to a dedicated Slack channel.
Facebook and Google Cloud BigQuery (REST) integration alternatives
About Facebook
Automate Facebook posting/engagement within Latenode workflows. Use it to monitor brand mentions, post content, or gather lead data automatically. Connect Facebook to other apps, like CRMs or data warehouses, to streamline social media management. Latenode's visual editor lets you design flexible scenarios without code, and its scaling architecture handles high volumes.
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About Google Cloud BigQuery (REST)
Automate BigQuery data workflows in Latenode. Query and analyze massive datasets directly within your automation scenarios, bypassing manual SQL. Schedule queries, transform results with JavaScript, and pipe data to other apps. Scale your data processing without complex coding or expensive per-operation fees. Perfect for reporting, analytics, and data warehousing automation.
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See how Latenode works
FAQ Facebook and Google Cloud BigQuery (REST)
How can I connect my Facebook account to Google Cloud BigQuery (REST) using Latenode?
To connect your Facebook account to Google Cloud BigQuery (REST) on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Facebook and click on "Connect".
- Authenticate your Facebook and Google Cloud BigQuery (REST) accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze Facebook ad performance in BigQuery?
Yes, you can! Latenode simplifies data transfer for in-depth Facebook Ads analysis in BigQuery. Use no-code blocks with JavaScript for custom metrics, improving your campaign insights.
What types of tasks can I perform by integrating Facebook with Google Cloud BigQuery (REST)?
Integrating Facebook with Google Cloud BigQuery (REST) allows you to perform various tasks, including:
- Backing up Facebook data to Google Cloud BigQuery (REST) for compliance.
- Analyzing user engagement metrics from Facebook in BigQuery.
- Automating data transfers for real-time reporting.
- Creating custom dashboards based on Facebook ad campaign data.
- Enriching BigQuery data with Facebook audience insights.
How do I handle errors during Facebook data transfer?
Latenode provides error logging and retry mechanisms, plus custom JavaScript blocks for data validation, ensuring reliable data transfer to BigQuery.
Are there any limitations to the Facebook and Google Cloud BigQuery (REST) integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Rate limits imposed by the Facebook API may affect data retrieval speed.
- Initial data transfer may require significant processing time.
- Some advanced Facebook data points might need custom JavaScript parsing.